Abstract.
We present novel space and time-efficient algorithms for finding frequent items over general update streams. Our algorithms are based on a novel adaptation of the popular dyadic intervals method for finding frequent items. The algorithms improve upon existing algorithms in both theory and practice.
1 Introduction
There is a growing class of applications in areas of business and scientific data processing that continuously monitor large volumes of rapidly arriving data for detecting user-programmed scenarios, some o ....etc

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Automatic Webpage Update Informer ....etc

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This article is presented by:
D. Chandrasekharam
Department of Earth Sciences
Indian Institute of Technology
Bombay 400076, India
GEOTHERMAL ENERGY RESOURCES OF INDIA: COUNTRY UPDATE

ABSTRACT
All the geothermal provinces of India are located in areas with high heat flow and geothermal gradients. The heat flow and thermal gradient values vary from 75–468 mW/m2 and 59–234°C respectively. Additional exploration studies and reservoir modelling have ....etc

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Abstract
This paper presents a new technique for online identificationof an induction motor rotor time constant. The techniqueis designed for a shaft-sensorless indirect field-oriented controlinduction motor drive with a model reference adaptive system(MRAS)-based speed estimator. The MRAS estimator is sensitiveto the changes in the rotor time constant, and online identificationof that parameter is essential. If rotor parameter error exists, itdoes not only change the achieved rotor speed, but it also changesthe dynamic behavior of the ....etc

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Want to show bengali karmasansthan paper of 10th march. ....etc

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Abstract.
We present deterministic sub-linear space algorithms for a number of problems over update data streams, including, estimating fre- quencies of items and ranges, ¯nding approximate frequent items and approximate Á-quantiles, estimating inner-products, constructing near- optimal B-bucket histograms and estimating entropy. We also present new lower bound results for several problems over update data streams.
1 Introduction
The data streaming model presents a computational model for a variety of monitoring a ....etc

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presented by:
Q. Ali Bakhtiar


GSM Location Update
Definitions
• Location Area (LA): A GSM network is divided into cells. A group of cells is considered a location area. A mobile phone in motion keeps the network informed about changes in the location area.
• Home Location Register (HLR):The HLR maintains a database for the mobile subscribers. At any point of time, the HLR knows the address of the MSC VLR that control the current location area of the mobile. The HLR is informed about a location area upda ....etc

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SSUM: Smart Server Update Mechanism For Maintaining Cache Consistency In Mobile Environments – Mobile Computing

This paper proposes a cache consistency scheme based on a previously proposed architecture for caching database data in MANETs. The original scheme for data caching stores the queries that are submitted by requesting nodes in special nodes, called query directories (QDs), and uses these queries to locate the data (responses) that are stored in the nodes that requested them, called caching nodes (CNs). The consistency scheme is ....etc

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ABSTRACT
There is growing interest in algorithms for processing and query- ing continuous data streams (i.e., data that is seen only once in a _xed order) with limited memory resources. Providing (perhaps approximate) answers to queries over such streams is a crucial re- quirement for many application environments; examples include large IP network installations where performance data from dif- ferent parts of the network needs to be continuously collected and analyzed. The ability to estimate the number of distinct (sub)tuples in the ....etc

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ABSTRACT
There is growing interest in algorithms for processing and querying continuous data streams (i.e., data that is seen only once in a _xed order) with limited memory resources. In its most general form, a data stream is actually an update stream, i.e., comprising data-item deletions as well as inser- tions. Such massive update streams arise naturally in several application domains (e.g., monitoring of large IP network installations, or processing of retail-chain transactions). Estimating the cardinality of set expressions de_ne ....etc

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